Economists have been venturing into the realm of human emotions for some years now. This column provides a unique approach to investigating the link between income and happiness. It finds that while money really can buy happiness, there are many other factors that can get in the way.

Anyone interested in the sources of joy and misery among (wo)mankind would do well turning to world literature. Tolstoy, of course, famously observed in Anna Karenina that “happy families are all alike; every unhappy family is unhappy in its own way” (Tolstoy 1877). Maybe this is why tragedy is often the more alluring genre.

But the research literature has been catching up. For the past half century, social scientists have been asking individuals questions about their wellbeing – how happy they are or how satisfied with their lives – and analysing the answers.

In almost every country in the world and throughout time the personal factors associated with happiness are pretty much the same:

women are happier than men,

the young and the old are happier than those of middle age,

more education, a stable job, marriage, and higher income are associated with more happiness.

A big question is why these associations exist. Does getting married make people happier or do those already more content simply make the better marriage partners? Does money buy happiness? Or are the cheerful more appealing to employers and therefore the ones who hold good jobs, and have higher earnings? Better looking and taller individuals earn more in the labour market (and, if they are professors, get better teaching evaluations from their students!), so it doesn’t seem unreasonable that the more cheery should earn more as well. If you were the boss on Sesame Street, who would you rather give a raise to: Elmo or Oscar the Grouch?

Does income cause happiness?

In order to make headway on the question whether income causes happiness you would like to manipulate the incomes of some people and then check whether the newly enriched report higher wellbeing. Lottery winnings are one such source of random changes to individual incomes and have been analysed by Gardner and Oswald (2007). But data on lottery winners are scarce, and large wins in the available data are rare. Winners do a bit better on a depression scale but the results are far from conclusive.

In a recent paper (Pischke 2011), I have been using a different approach. I am exploiting the fact that similar workers employed in different sectors of the economy tend to earn different wages. Wages are generally higher in more capital- and skill-intensive industries and in industries which are less competitive. These attributes tend to be associated with higher profits for the firms, and some of these profits are shared with the employees. Legal services, communications, and mining tend to be high-paying sectors, while workers in personal services, education, and repair services tend to be paid poorly. The differences between the extremes are large. They can easily reach 50% or more after accounting for workers’ education and age. They are also rather permanent as workers tend to stay in their industry for many years.

A new empirical strategy

The idea of my research is to treat those working in the high-paying sectors as the winners in the job market lottery. It turns out that the increase in happiness you get by comparing the average happiness to the average family incomes across sectors of the economy is about the same as if you compare the happiness of individuals with different incomes directly. If industry affiliation is truly a lottery then this suggests that the usual association between money and happiness reflects the fact that money can buy you this happiness – not simply that employers pay Elmo better than Oscar.

I do various things in order to probe whether it is reasonable to think of working in a high- or low-paying sector truly as a lottery, or whether the association is driven by other factors (maybe the happy are more attractive to employers in well-paying industries). One method is to look at the happiness of married women and exploiting income variation associated with the industry her husband works in. If factors other than money drive the correlation between average industry income and average wellbeing, one would expect the relationship to be muted for women. But I find basically the same association for married women as for men themselves. This bolsters the conclusion that the causality really runs from money to happiness.

Rich or poor, it’s always nice to have money; especially more than others

But like many things in life, money may be a double-edged sword. While the evidence is mounting that it makes us happier, this might only work if others don’t make more money as well.

In other words, people like more money not just because it buys us more things but also because it lets us step up the social ladder and get ahead of those around us. That this might be important in explaining the data on individual wellbeing was famously noted in a paper by Richard Easterlin in 1974. Easterlin was perplexed by the finding that income correlates with happiness within countries but he found little or no relationship between economic growth at the country level and people’s happiness.

If money buys happiness you would expect that economic growth does the same at the country level. Easterlin resolved this paradox – now named after him – with the idea that individuals get happier if they are richer but our happiness is reduced when everyone else around us gets richer. In other words, people seem to care about their status or relative standing in the community. As the economy gets richer, our position in the social hierarchy stays the same. It’s much like the hamster spinning inside its wheel. The hamster runs only to stand still.

Direct evidence on the relative-income hypothesis

While the relative-income hypothesis is appealing and confirmed by correlations in the data as well, direct evidence has been scant until recently. You would ideally want to manipulate the income of the Jones’ to see what happens to our own wellbeing. Peter Kuhn from the University of California at Santa Barbara and a group of Dutch researchers have looked at this in the rather unique Dutch postcode lottery (Kuhn et al. 2008). Every week the lottery picks a postal code consisting of about 20 households. Lottery ticket holders living in this postal code win a cash prize of €12,500 and one participant wins a BMW.

The researchers compare lottery ticket holders in winning postcodes to ticket holders in non-winning postcodes to isolate the effect of a change in income. They also compare non-ticket holders in a winning postcode to non-ticket holders in a non-winning postcode to isolate the social effects such as jealousy. They don’t find any effect of lottery winnings on the happiness of either group. This is consistent with relative income mattering for the winners (after all, they live next to seven other winners on average) but does not point towards income comparisons for the non-ticket holders, who should be more miserable when their neighbours win.

But the Dutch samples are small, and maybe neighbours are not the most important comparison group. In fact, much points towards co-workers being the group with which most individuals might compare themselves. David Card, another researcher at the University of California at Berkeley, and his collaborators have looked at this effect recently in a neat study (Card et al. 2010). The decision of a California court on the state’s “right to know law” led a newspaper, the Sacramento Bee, to establish a website with salary information on every State of California employee.

The researchers surveyed a sample of University of California employees (part of the state’s public sector) about their job satisfaction and intentions to quit. Beforehand, they had informed a random subset of their survey participants of the Sacramento Bee website. Many (though not all) employees learned about the website in this way and started to look up their co-worker pay. The employees who learned about the website through the experiment reported lower job satisfaction and were more likely to want to look for a new job if they earned less than the median in the unit of the university where they work. There was no effect on workers above the median.

So the evidence on the importance of social comparisons is still sparse and somewhat ambiguous but the California study suggests some interesting effects.

Concluding remarks

A final caveat is necessary when thinking about the effects of income on wellbeing.

There are many sources of happiness or gloom, and money is only one of them.

While money seems to matter it is responsible at most for a small part of our overall wellbeing.

As far as all the other determinants are concerned, we have a sense that social interactions and relationships seem to matter. But on this, the research literature is at most beginning to scratch the surface. So if you want to know about the multitude of sources for human joy and misery, Tolstoy, Dickens, et al. will probably remain your main reference for a quite a while to come.